European Journal of Forest Research

, Volume 134, Issue 6, pp 1055–1074 | Cite as

New procedure for the simulation of belowground competition can improve the performance of forest simulation models

  • Vladimir Shanin
  • Raisa Mäkipää
  • Maxim Shashkov
  • Natalya Ivanova
  • Konstantin Shestibratov
  • Svetlana Moskalenko
  • Liliya Rocheva
  • Pavel Grabarnik
  • Kapitolina Bobkova
  • Alexey Manov
  • Andrey Osipov
  • Elvira Burnasheva
  • Maria Bezrukova
Original Paper

Abstract

The major part of existing models of belowground competition in mixed forest stands is limited in explaining the spatial distribution of roots as a response to competitive pressure from neighbours and heterogeneity of soil properties. We are presenting a new spatially explicit and multi-layered discrete model of belowground competition, RootInt (ROOTs INTake). It describes spatial distribution of belowground biomass and allows simulation of competition between trees for soil nutrients. The tree-specific area of root zone is calculated on the basis of stem diameter, with site-specific modifiers to account for the effect of soil fertility and moisture. The shape of root zone is dependent on the amount of available nitrogen in the current cell, distance between this cell and the stem base, and the mass of roots of other plants. RootInt was incorporated into ecosystem model EFIMOD to refine the existing description of belowground competition in forest stands with multiple cohorts and tree species. The results of simulation showed that bringing more complexity into structure of stand (including initial spatial locations of trees, species composition and age structure, vertical structure of canopy) resulted in higher spatial variation in competition intensity, as well as in higher rates of resource uptake. This indicates that stands with complex canopy structure had high plasticity in their root systems and were adapted to intensive competition for soil resources.

Keywords

Process-based model Root systems Forest ecosystems Adaptation Meta-analysis 

Supplementary material

10342_2015_909_MOESM1_ESM.pdf (759 kb)
Supplementary material 1 (PDF 759 kb)

References

  1. Abrazhko MA (1982) The response of spruce fine roots on excluding of belowground competition from neighbouring trees [Reakcija tonkih kornej eli na iskljuchenie kornevoj konkurencii sosednih derev’ev]. Lesovedenie 6:41–46 (In Russian) Google Scholar
  2. Adler RJ (1981) The geometry of random fields. SIAM-Society for Industrial and Applied Mathematics, Philadelphia, p 280Google Scholar
  3. Ammer C, Wagner S (2005) An approach for modelling the mean fine-root biomass of Norway spruce stands. Trees 19:145–153CrossRefGoogle Scholar
  4. Baneva NA (1980) Changes in mass of spruce fine roots in pure stands [Izmenenie massy melkih kornej eli v chistyh drevostojah]. Lesovedenie 1:86–89 (In Russian) Google Scholar
  5. BassiriRad H (2005) Nutrient acquisition by plants: an ecological perspective. Ecological Studies, Vol. 181. Springer, p 348Google Scholar
  6. Bezrukova MG, Shanin VN, Mikhailov AV, Mikhailova NV, Khoraskina YS, Grabarnik PY, Komarov AS (2012) DLES: a component-based framework for ecological modeling. In: Jordan F, Jørgensen SE (eds) Models of the ecological hierarchy: from molecules to the ecosphere. Developments in environmental modelling series, V.25. Elsevier Science, Amsterdam, pp 331–354CrossRefGoogle Scholar
  7. Bielak K, Dudzińska M, Pretzsch H (2014) Mixed stands of Scots pine (Pinus sylvestris L.) and Norway spruce [Picea abies (L.) Karst] can be more productive than monocultures. Evidence from over 100 years of observation of long-term experiments. For Syst 23:573–789Google Scholar
  8. Bobbink R, Hicks K, Galloway J, Spranger T, Alkemade R, Ashmore M, Bustamante M, Cinderby S, Davidson E, Dentener F, Emmett B, Erisman J-W, Fenn M, Gilliam F, Nordin A, Pardo L, De Vries W (2010) Global assessment of nitrogen deposition effects on terrestrial plant diversity: a synthesis. Ecol Appl 20(1):30–59PubMedCrossRefGoogle Scholar
  9. Bobkova KS (1971) The structure of root systems of tree species in different types of pine forests of Zelenoborsky station [Stroenie kornevyh sistem drevesnyh porod v razlichnyh tipah sosnovyh lesov Zelenoborskogo stacionara]. Proc Komi Branch Acad Sci USSR 24:52–69 (In Russian) Google Scholar
  10. Bolte A, Villanueva I (2006) Interspecific competition impacts on the morphology and distribution of fine roots in European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.). Eur J For Res 125(1):15–26CrossRefGoogle Scholar
  11. Brandtberg P-O, Bengtsson J, Lundkvist H (2004) Distributions of the capacity to take up nutrients by Betula spp. and Picea abies in mixed stands. For Ecol Manage 198:193–208CrossRefGoogle Scholar
  12. Brassard BW, Chen HYH, Bergeron Y, Paré D (2011) Differences in fine root productivity between mixed- and single-species stands. Funct Ecol 25:238–246CrossRefGoogle Scholar
  13. Brunner I, Bakker MR, Björk RG, Hirano Y, Lukac M, Aranda X, Børja I, Eldhuset TD, Helmisaari H-S, Jourdan C, Konôpka B, López BC, Pérez CM, Persson H, Ostonen I (2013) Fine-root turnover rates of European forests revisited: an analysis of data from sequential coring and ingrowth cores. Plant Soil 362:357–372CrossRefGoogle Scholar
  14. Burton AJ, Pregitzer KS, Hendrick RL (2000) Relationships between fine root dynamics and nitrogen availability in Michigan northern hardwood forests. Oecologia 125:389–399CrossRefGoogle Scholar
  15. Butterbach-Bahl K, Gundersen P, Ambus P, Augustin J, Beier C, Boeckx P, Dannermann M, Gimenso BS, Kiese R, Kitzler B, Ibrom A, Rees RM, Smith KA, Stevens C, Vesala T, Zechmeister-Boltenstern S (2011) Nitrogen processes in terrestrial ecosystems. In: Sutton MA, Howard CM, Erisman JW, Billen G, Bleeker A, van Grinsven H, Grizzetti B (eds) The European nitrogen assessment: sources, effects, and policy perspectives. Cambridge University Press, Cambridge, pp 99–125CrossRefGoogle Scholar
  16. Cadisch G, de Willigen P, Suprayogo D, Mobbs DC, van Noordwijk M, Rowe EC (2004) Catching and competing for mobile nutrients in soils. In: van Noordwijk M, Cadisch G, Ong CK (eds) Below-ground interactions in tropical agroecosystems: concepts and models with multiple plant components. CABI, Cabazon, pp 171–191CrossRefGoogle Scholar
  17. Campbell BD, Grime JP, Mackey JML, Jalili A (1991) A trade-off between scale and precision in resource foraging. Oecologia 87:532–538CrossRefGoogle Scholar
  18. Casper BB, Jackson RB (1997) Plant competition underground. Ann Rev Ecol Evol Syst 28:545–570CrossRefGoogle Scholar
  19. Casper BB, Schenk HJ, Jackson RB (2003) Defining a plant’s belowground zone of influence. Ecology 84(9):2313–2321CrossRefGoogle Scholar
  20. Cavard X, Bergeron Y, Chen HYH, Paré D, Laganière J, Brassard B (2011) Competition and facilitation between tree species change with stand development. Oikos 120:1683–1695CrossRefGoogle Scholar
  21. Chen H, Harmon ME, Griffiths RP (2001) Decomposition and nitrogen release from decomposing woody roots in coniferous forests of the Pacific Northwest: a chronosequence approach. Can J For Res 31:246–260CrossRefGoogle Scholar
  22. Chertov OG, Komarov AS, Nadporozhskaya MA, Bykhovets SS, Zudin SL (2001) ROMUL—a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modelling. Ecol Model 138:289–308CrossRefGoogle Scholar
  23. Coomes DA, Grubb PJ (2000) Impacts of root competition in forests and woodlands: a theoretical framework and review of experiments. Ecol Monogr 70(2):171–207CrossRefGoogle Scholar
  24. Daniels RF, Burkhart HE, Clason TR (1986) A comparison of competition measures for predicting growth of loblolly pine trees. Can J For Res 16:1230–1237CrossRefGoogle Scholar
  25. Deckmyn G, Meyer A, Smits MM, Ekblad A, Grebenc T, Komarov A, Kraigher H (2014) Simulating ectomycorrhizal fungi and their role in carbon and nitrogen cycling in forest ecosystems. Can J For Res 44:535–553CrossRefGoogle Scholar
  26. DesRochers A, Lieffers VJ (2001) The coarse-root system of mature Populus tremuloides in declining stands in Alberta, Canada. J Veg Sci 12:355–360CrossRefGoogle Scholar
  27. Diggle P (1983) Statistical analysis of spatial point patterns. Academic Press, London, p 159Google Scholar
  28. Dupuy L, Fourcaud T, Stokes A, Danjon F (2005) A density-based approach for the modelling of root architecture: application to maritime pine (Pinus pinaster Ait.) root systems. J Theor Biol 236:323–334PubMedCrossRefGoogle Scholar
  29. Fahey TJ, Hughes JW (1994) Fine root dynamics in a northern hardwood forest ecosystem, Hubbard Brook Experimental Forest, NH. J Ecol 82:533–548CrossRefGoogle Scholar
  30. Feddes RA, Raats PAC (2004) Parameterizing the soil–water–plant root system. In: Feddes RA, de Rooij GH, van Dam JC (eds) Unsaturated-zone modeling: progress, challenges and applications. Wageningen UR Frontis Series, Vol. 6, XXII. pp 95–141Google Scholar
  31. Finér L, Helmisaari H-S, Lõhmus K, Majdi H, Brunner I, Børja I, Eldhuset T, Godbold D, Grebenc T, Konôpka B, Kraigher H, Möttönen M-R, Ohashi M, Oleksyn J, Ostonen I, Uri V, Vanguelova E (2007) Variation in fine root biomass of three European tree species: beech (Fagus sylvatica L.), Norway spruce (Picea abies L. Karst.), and Scots pine (Pinus sylvestris L.). Plant Biosyst 141(3):394–405CrossRefGoogle Scholar
  32. Finér L, Ohashi M, Noguchi K, Hirano Y (2011a) Factors causing variation in fine root biomass in forest ecosystems. For Ecol Manage 261:265–277CrossRefGoogle Scholar
  33. Finér L, Ohashi M, Noguchi K, Hirano Y (2011b) Fine root production and turnover in forest ecosystems in relation to stand and environmental characteristics. For Ecol Manage 262:2008–2023CrossRefGoogle Scholar
  34. Fransen B, de Kroon H, Berendse F (2001) Soil nutrient heterogeneity alters competition between two perennial grass species. Ecology 82(9):2534–2546CrossRefGoogle Scholar
  35. Gale MR, Grigal DF (1987) Vertical root distributions of northern tree species in relation to successional status. Can J For Res 17:829–834CrossRefGoogle Scholar
  36. Gao SY, Pan WL, Koenig RT (1998) Integrated root system age in relation to plant nutrient uptake activity. Agron J 90:505–510CrossRefGoogle Scholar
  37. Gärtner H, Wagner B, Heinrich I, Denier C (2009) 3D-laser scanning: a new method to analyze coarse tree root systems. For Snow Landsc Res 82:95–106Google Scholar
  38. Gayler S, Grams TEE, Kozovits AR, Winkler JB, Luedemann G, Priesack E (2006) Analysis of competition effects in mono- and mixed cultures of juvenile beech and spruce by means of the plant growth simulation model PLATHO. Plant Biol 8:503–514PubMedCrossRefGoogle Scholar
  39. Gill RA, Jackson RB (2000) Global patterns of root turnover for terrestrial ecosystems. New Phytol 147:13–31CrossRefGoogle Scholar
  40. Giniyatullin RKh, Kulagin AYu (2012) State of the roots system of the birch Betula pendula Roth. in the conditions of Sterlitamak industrial centre [Sostojanie kornevoj sistemy berezy povisloj (Betula pendula Roth.) v uslovijah Sterlitamakskogo promyshlennogo centra]. Bull Udmurt Univ 4:21–28 (In Russian) Google Scholar
  41. Goreaud F, Loreau M, Millier C (2002) Spatial structure and the survival of an inferior competitor: a theoretical model of neighbourhood competition in plants. Ecol Model 158:1–19CrossRefGoogle Scholar
  42. Graham BF, Bormann FH (1966) Natural root grafts. Bot Rev 32(3):255–292CrossRefGoogle Scholar
  43. Grime JP (2002) Plant strategies, vegetation processes, and ecosystem properties, 2nd edn. Wiley, Chichester, p 417Google Scholar
  44. Gross K, Peters A, Pregitzer KS (1993) Fine root growth and demographic responses to nutrient patches in four old-field plant species. Oecologia 95:61–64CrossRefGoogle Scholar
  45. Grote R, Pretzsch H (2002) A model for individual tree development based on physiological processes. Plant Biol 4:167–180CrossRefGoogle Scholar
  46. Haefner JW, Poole GC, Dunn PV, Decker RT (1991) Edge effects in computer models of spatial competition. Ecol Model 56:221–244CrossRefGoogle Scholar
  47. Hansson K, Helmisaari H-S, Sah SP, Lange H (2013) Fine root production and turnover of tree and understorey vegetation in Scots pine, silver birch and Norway spruce stands in SW Sweden. For Ecol Manage 309:58–65CrossRefGoogle Scholar
  48. Hartmann P, von Wilpert K (2014) Fine-root distributions of Central European forest soils and their interaction with site and soil properties. Can J For Res 44:71–81CrossRefGoogle Scholar
  49. Helmisaari H-S, Makkonen K, Kellomäki S, Valtonen E, Mälkönen E (2002) Below- and above-ground biomass, production and nitrogen use in Scots pine stands in Eastern Finland. For Ecol Manage 165:317–326CrossRefGoogle Scholar
  50. Helmisaari H-S, Derome J, Nöjd P, Kukkola M (2007) Fine root biomass in relation to site and stand characteristics in Norway spruce and Scots pine stands. Tree Physiol 27:1493–1504PubMedCrossRefGoogle Scholar
  51. Helmisaari H-S, Sah S, Aro L (2009) Fine roots on intensive forest ecosystem monitoring plots FIP4, FIP10 and FIP11 on Olkiluoto island in 2008. Finnish Forest Research Institute, Working Report 2009-127, p 33Google Scholar
  52. Hendricks JJ, Nadelhoffer KJ, Aber JD (1993) Assessing the role of fine roots in carbon and nutrient cycling. Trends Ecol Evol 8(5):174–178PubMedCrossRefGoogle Scholar
  53. Illian J, Penttinen A, Stoyan H, Stoyan D (2008) Statistical analysis and modelling of spatial point patterns. Wiley, Chichester, p 560Google Scholar
  54. Jackson RB, Manwaring JH, Caldwell MM (1990) Rapid physiological adjustment of roots to localized soil enrichment. Nature 344:58–60PubMedCrossRefGoogle Scholar
  55. Jackson RB, Sperry JS, Dawson TE (2000) Root water uptake and transport: using physiological processes in global predictions. Trends Plant Sci 5:482–488PubMedCrossRefGoogle Scholar
  56. Jose S, Williams R, Zamora D (2006) Belowground ecological interactions in mixed-species forest plantations. For Ecol Manage 233:231–239CrossRefGoogle Scholar
  57. Kalela EK (1949) On the horizontal roots in pine and spruce stands I. Acta For Fenn 57(2):1–79Google Scholar
  58. Kalela EK (1954) Pine seed trees and tree root relations [Mäntysiemenpuiden ja puustojen juurisuhteista]. Acta For Fenn 61(28):1–17 (In Finnish) Google Scholar
  59. Kalliokoski T (2011) Root system traits of Norway spruce, Scots pine, and silver birch in mixed boreal forests: an analysis of root architecture, morphology, and anatomy. Dissertation, Dissertationes Forestales 121. Vantaa, p 67Google Scholar
  60. Kalliokoski T, Nygren P, Sievänen R (2008) Coarse root architecture of three boreal tree species growing in mixed stands. Silva Fenn 42(2):189–210CrossRefGoogle Scholar
  61. Kalliokoski T, Sievänen R, Nygren P (2010) Tree roots as self-similar branching structures: axis differentiation and segment tapering in coarse roots of three boreal forest tree species. Trees 24:219–236CrossRefGoogle Scholar
  62. Komarov AS, Chertov OG, Zudin SL, Nadporozhskaya MA, Mikhailov AV, Bykhovets SS, Zudina EV, Zoubkova EV (2003) EFIMOD 2—a model of growth and cycling of elements in boreal forest ecosystems. Ecol Model 70:373–392CrossRefGoogle Scholar
  63. Külla T, Lõhmus K (1999) Influence of cultivation method on root grafting in Norway spruce (Picea abies (L.) Karst.). Plant Soil 217:91–100CrossRefGoogle Scholar
  64. Laitakari E (1929) The root system of pine (Pinus silvestris): a morphological investigation [Männyn juuristo. Morfologinen tutkimus.]. Acta For Fenn 33(1):1–380 (In Finnish) Google Scholar
  65. Laitakari E (1935) The root system of birch (Betula verrucosa and odorata) [Coivun juuristo]. Acta For Fenn 41(2):1–217 (In Finnish) Google Scholar
  66. Laschinkiy NN (1981) Structure and dynamics of pine forests of the Lower Angara region [Struktura i dinamika sosnovyh lesov Nizhnego Priangar’ja]. Nauka, Novosibirsk, p 272 (In Russian) Google Scholar
  67. LeBauer DS, Treseder KK (2008) Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. Ecology 89:371–379PubMedCrossRefGoogle Scholar
  68. Lebedev EV (2012) Productivity of the white birch organisms in the process of ontogenesis in the European part of Russia [Produktivnost’ berezy beloj na urovne organizma v ontogeneze v evropejskoj chasti Rossii]. Izvestia Orenburg State Agrarian University 4(36):18–22 (In Russian) Google Scholar
  69. Lebedev VM, Lebedev EV (2012) The relationship between biological productivity and nutritional activity of roots of conifers in Russian south taiga [Vzaimosvjaz’ biologicheskoj produktivnosti i poglotitel’noj dejatel’nosti kornej hvojnyh porod v ontogeneze v zone juzhnoj tajgi Rossii]. Agrohimija 8:9–17 (In Russian) Google Scholar
  70. Lõhmus K, Ivask M (1995) Decomposition and nitrogen dynamics of fine roots of Norway spruce (Picea abies (L.) Karst.) at different sites. Plant Soil 168–169:89–94CrossRefGoogle Scholar
  71. Lozinov GL (1980) Features of spatial distribution of underground parts of plants in forest biogeocoenoses of Moscow region [Osobennosti prostranstvennogo raspredelenija podzemnyh chastej rastenij v lesnyh biogeocenozah Podmoskov’ja]. Lesovedenie 1:58–63 (In Russian) Google Scholar
  72. Majdi H, Persson H (1993) Spatial distribution of fine roots, rhizosphere and bulk-soil chemistry in an acidified Picea abies stand. Scand J For Res 8:147–155CrossRefGoogle Scholar
  73. Mälkönen E (1974) Annual primary production and nutrient cycle in some Scots pine stands. Finnish Forest Research Institute, Helsinki 87 p Google Scholar
  74. Mälkönen E (1977) Annual primary production and nutrient cycle in a birch stand. Finnish Forest Research Institute, Helsinki 35 p Google Scholar
  75. Mao Z, Saint-André L, Bourrier F, Stokes A, Cordonnier T (2015) Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems. Ann Bot 116(2):261–277PubMedCrossRefGoogle Scholar
  76. Marklund LG (1988) Biomass functions for pine, spruce and birch in Sweden [Biomassafunktioner för tall, gran och björk i Sverige]. Department of Forest Survey. Swedish University of Agricultural Sciences, Umeå, Rep. No. 45, p 73 (In Swedish) Google Scholar
  77. Melin Y, Petersson H, Nordfjell T (2009) Decomposition of stump and root systems of Norway spruce in Sweden: a modelling approach. For Ecol Manage 257:1445–1451CrossRefGoogle Scholar
  78. Meyer A, Grote R, Butterbach-Bahl K (2012) Integrating mycorrhiza in a complex model system: effects on ecosystem C and N fluxes. Eur J For Res 131:1809–1831CrossRefGoogle Scholar
  79. Miina J, Pukkala T (2002) Application of ecological field theory in distance-dependent growth modelling. For Ecol Manage 161:101–107CrossRefGoogle Scholar
  80. Müller KH, Wagner S (2003) Fine root dynamics in gaps of Norway spruce stands in the German Ore Mountains. Forestry 76(2):149–158CrossRefGoogle Scholar
  81. O’Brien EE, Brown JS, Moll JD (2007) Roots in space: a spatially explicit model for below-ground competition in plants. Proc R Soc B 274:929–934PubMedCentralPubMedCrossRefGoogle Scholar
  82. Ostonen I, Lõhmus K, Helmisaari H-S, Truu J, Meel S (2007) Fine root morphological adaptations in Scots pine, Norway spruce and silver birch along a latitudinal gradient in boreal forests. Tree Physiol 27:1627–1634PubMedCrossRefGoogle Scholar
  83. Pagès L, Doussan C, Vercambre G (2000) An introduction on below-ground environment and resource acquisition, with special reference on trees. Simulation models should include plant structure and function. Ann For Sci 57:513–520CrossRefGoogle Scholar
  84. Park BB, Yanai RD, Fahey TJ, Bailey SW, Siccama TG, Shanley JB, Cleavitt NL (2008) Fine root dynamics and forest production across a calcium gradient in northern hardwood and conifer ecosystems. Ecosystems 11:325–341CrossRefGoogle Scholar
  85. Persson H, von Fircks Y, Majdi H, Nilsson LO (1995) Root distribution in a Norway spruce (Picea abies (L.) Karst.) stand subjected to drought and ammonium-sulphate application. Plant Soil 168–169:161–165CrossRefGoogle Scholar
  86. Petersson H, Ståhl G (2006) Functions for below-ground biomass of Pinus sylvestris, Picea abies, Betula pendula and Betula pubescens in Sweden. Scand J For Res 21(7):84–93CrossRefGoogle Scholar
  87. Piñeiro G, Perelman S, Guerschman JP, Paruelo JM (2008) How to evaluate models: Observed versus predicted or predicted versus observed? Ecol Model 216:316–322CrossRefGoogle Scholar
  88. Pretzsch H, Schütze G (2014) Size-structure dynamics of mixed versus pure forest stand. Forest Syst 23(3):560–572CrossRefGoogle Scholar
  89. Pretzsch H, Heym M, Pinna S, Schneider R (2014) Effect of variable retention cutting on the relationship between growth of coarse roots and stem of Picea mariana. Scan J For Res 29:222–233Google Scholar
  90. Pretzsch H, del Río M, Ammer Ch, Avdagic A, Barbeito I, Bielak K, Brazaitis G, Coll L, Dirnberger G, Drössler L, Fabrika M, Forrester DI, Godvod K, Heym M, Hurt V, Kurylyak V, Löf M, Lombardi F, Matović B, Mohren F, Motta R, den Ouden J, Pach M, Ponette Q, Schütze G, Schweig J, Skrzyszewski H, Sramek V, Sterba H, Stojanović D, Svoboda M, Vanhellemont M, Verheyen K, Wellhausen K, Zlatanov T, Bravo-Oviedo A (2015) Growth and yield of mixed versus pure stands of Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) analysed along a productivity gradient through Europe. Eur J For Res 134:927–947CrossRefGoogle Scholar
  91. Puhe J (2003) Growth and development of the root system of Norway spruce (Picea abies) in forest stands: a review. For Ecol Manage 175:253–273CrossRefGoogle Scholar
  92. Püttsepp Ü, Lõhmus K, Persson HÅ, Ahlström K (2006) Fine-root distribution and morphology in an acidic Norway spruce (Picea abies (L.) Karst.) stand in SW Sweden in relation to granulated wood ash application. For Ecol Manage 221:291–298CrossRefGoogle Scholar
  93. Raynaud X, Leadley PW (2005) Symmetry of belowground competition in a spatially explicit model of nutrient competition. Ecol Model 189:447–453CrossRefGoogle Scholar
  94. Roose T (2000) Mathematical model of plant nutrient uptake. Dissertation, Linacre College, University of Oxford, Michaelmas, p 226Google Scholar
  95. Rothe A, Binkley D (2001) Nutritional interactions in mixed species forests: a synthesis. Can J For Res 31:1855–1870CrossRefGoogle Scholar
  96. Salas E, Ozier-Lafontaine H, Nygren P (2004) A fractal model applied for estimating root biomass and architecture in two tropical legume tree species. Ann For Sci 61:337–345CrossRefGoogle Scholar
  97. Sannikov SN, Sannikova NS (2014) Forest as underground-closed dendrocenoecosystem [Les kak podzemno-somknutaja dendrocenojekosistema]. Sibirskiy lesnoy zhurnal 1:25–34 (In Russian) Google Scholar
  98. Schenk MK (1996) Regulation of nitrogen uptake on the whole plant level. Plant Soil 181:131–137CrossRefGoogle Scholar
  99. Schiffers K, Tielbörger K, Tietjen B, Jeltsch F (2011) Root plasticity buffers competition among plants: theory meets experimental data. Ecology 92(3):610–620PubMedCrossRefGoogle Scholar
  100. Schlather M (2001) Simulation and analysis of random fields. R News 1(2):18–20Google Scholar
  101. Schmid I (2002) The influence of soil type and interspecific competition on the fine root system of Norway spruce and European beech. Basic Appl Ecol 3:339–346CrossRefGoogle Scholar
  102. Schmid I, Kazda M (2002) Root distribution of Norway spruce in monospecific and mixed stands on different soils. For Ecol Manage 159(1–2):37–47CrossRefGoogle Scholar
  103. Seidl R, Rammer W, Scheller RM, Spies TA (2012) An individual-based process model to simulate landscape-scale forest ecosystem dynamics. Ecol Model 231:87–100CrossRefGoogle Scholar
  104. Shanin VN (2015) The analysis of lateral spreading of tree roots in different forest types. [Analiz gorizontal’nogo rasprostranenija kornej derev’ev v raznyh tipah lesa]. Lesovedenie 2:130–139 (In Russian) Google Scholar
  105. Shanin VN, Komarov AS, Mäkipää R (2014) Tree species composition affects productivity and carbon dynamics of different site types in boreal forests. Eur J For Res 133:273–286CrossRefGoogle Scholar
  106. Shanin VN, Rocheva LK, Shashkov MP, Ivanova NV, Moskalenko SV, Burnasheva ER (2015) Spatial distribution of root biomass of certain tree species (Picea abies, Pinus sylvestris, Betula sp.). Biol Bull 42(3):260–268CrossRefGoogle Scholar
  107. Shestibratov K, Lebedev V, Podrezov A, Salmova M (2011) Transgenic aspen and birch trees for Russian plantation forests. BMC Proc 5(Suppl 7):P124PubMedCentralCrossRefGoogle Scholar
  108. Shvidenko A, Shchepashchenko DG, Nilsson S, Buluy YI (2008) Tables and models of growth and productivity of forests of major forest forming species of Northern Eurasia (standard and reference materials). Federal Agency of Forest Management, Moscow, p 886Google Scholar
  109. Silver WL, Miya RK (2001) Global patterns in root decomposition: comparisons of climate and litter quality effects. Oecologia 129:407–419CrossRefGoogle Scholar
  110. Šimůnek J, Hopmans JW (2009) Modeling compensated root water and nutrient uptake. Ecol Model 220:505–521CrossRefGoogle Scholar
  111. Smith M, Burgess SSO, Suprayogo D, Lusiana B, Widianto H (2004) Uptake, partitioning and redistribution of water by roots in mixed-species agroecosystems. In: van Noordwijk M, Cadisch G, Ong CK (eds) Below-ground interactions in tropical agroecosystems: concepts and models with multiple plant components. CABI, Cabazon, pp 157–170CrossRefGoogle Scholar
  112. Sperry JS, Adler ER, Campbell GS, Comstock JP (1998) Limitation of plant water use by rhizosphere and xylem conductance: results from a model. Plant Cell Environ 21:347–359CrossRefGoogle Scholar
  113. Strong WL, LaRoi GH (1985) Root density—soil relationships in selected boreal forests of central Alberta, Canada. For Ecol Manage 12:233–251CrossRefGoogle Scholar
  114. Tamm CO (1991) Nitrogen in terrestrial ecosystems. Springer-Verlag, Berlin-Heidelberg, p 115CrossRefGoogle Scholar
  115. Tanskanen N, Ilvesniemi H (2007) Spatial distribution of fine roots at ploughed Norway spruce forest sites. Silva Fenn 41(1):45–54CrossRefGoogle Scholar
  116. Tarroux E, DesRochers A (2010) Frequency of root grafting in naturally and artificially regenerated stands of Pinus banksiana: influence of site characteristics. Can J For Res 40:861–871CrossRefGoogle Scholar
  117. Tarroux E, DesRochers A, Krause C (2010) Effect of natural root grafting on growth response of jack pine (Pinus banksiana) after commercial thinning. For Ecol Manage 260:526–535CrossRefGoogle Scholar
  118. Tarroux E, DesRochers A, Tremblay F (2014) Molecular analysis of natural root grafting in jack pine (Pinus banksiana) trees: How does genetic proximity influence anastomosis occurrence? Tree Genet Genomes 10:667–677CrossRefGoogle Scholar
  119. Terekhov GG, Usoltsev VA (2010) Morphological structure of plantations and root density in the rhizosphere of spruce plantations and secondary deciduous stand on Middle Ural as a characteristics of competition [Morfostruktura nasazhdenij i kornenasyshhennost’ rizosfery kul’tur eli sibirskoj i vtorichnogo listvennogo drevostoja na Srednem Urale kak harakteristika ih konkurentnyh otnoshenij]. Hvojnye boreal’noj zony XXVII(3–4):330–335 (In Russian) Google Scholar
  120. Tobin B, Čermák J, Chiatante D, Danjon F, di Iorio A, Dupuy L, Eshel A, Jourdan C, Kalliokoski T, Laiho R, Nadezhdina N, Nicoll B, Pagès L, Silva J, Spanos I (2007) Towards developmental modelling of tree root systems. Plant Biosyst 141(3):481–501CrossRefGoogle Scholar
  121. Urban J, Čermák J, Ceulemans R (2015) Above- and below-ground biomass, surface and volume, and stored water in a mature Scots pine stand. Eur J For Res 134:61–74CrossRefGoogle Scholar
  122. van Wijk MT, Rodriguez-Iturbe I (2002) Tree-grass competition in space and time: insights from a simple cellular automata model based on ecohydrological dynamics. Water Resour Res 38(9):18-1–18-15CrossRefGoogle Scholar
  123. Verkholantseva LA, Bobkova KS (1972) The effect of soil environment of root systems of tree species in spruce plantations in Northern taiga [Vlijanie pochvennyh uslovij na kornevye sistemy drevesnyh porod v elovyh nasazhdenijah podzony severnoj tajgi]. Scientific reports 6, Syktyvkar, p 56 (In Russian) Google Scholar
  124. Vitousek PM, Howarth RW (1991) Nitrogen limitation on land and in the sea: How can it occur? Biogeochemistry 13:87–115CrossRefGoogle Scholar
  125. Vomperskiy SE (1959) Specific features of structure of root systems in Pinus sylvestris L. on drained peaty soils [Osobennosti stroenija kornevyh sistem Pinus sylvestris L. na osushenyh torfjanyh pochvah]. Botanicheskij zhurnal 1:79–87 (In Russian) Google Scholar
  126. Warren JM, Hanson PJ, Iversen CM, Kumar J, Walker AP, Wullschleger SD (2014) Root structural and functional dynamics in terrestrial biosphere models—evaluation and recommendations. New Phytol 205:59–78PubMedCrossRefGoogle Scholar
  127. Wu H, Sharpe PJH, Walker J, Penridge LK (1985) Ecological field theory: a spatial analysis of resource interference among plants. Ecol Model 29:215–243CrossRefGoogle Scholar
  128. Yuan ZY, Chen HYH (2010) Fine root biomass, production, turnover rates, and nutrient contents in boreal forest ecosystems in relation to species, climate, fertility, and stand age: literature review and meta-analyses. Crit Rev Plant Sci 29:204–221CrossRefGoogle Scholar
  129. Zheldak VI, Atrokhin VG (2003) Forestry [Lesovodstvo]. Moscow, VNIILM, p 336 (In Russian) Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Vladimir Shanin
    • 1
  • Raisa Mäkipää
    • 2
  • Maxim Shashkov
    • 1
  • Natalya Ivanova
    • 3
  • Konstantin Shestibratov
    • 4
  • Svetlana Moskalenko
    • 1
  • Liliya Rocheva
    • 5
  • Pavel Grabarnik
    • 1
  • Kapitolina Bobkova
    • 6
  • Alexey Manov
    • 6
  • Andrey Osipov
    • 6
  • Elvira Burnasheva
    • 7
  • Maria Bezrukova
    • 1
  1. 1.Institute of Physicochemical and Biological Problems in Soil ScienceRussian Academy of SciencesPushchinoRussia
  2. 2.Natural Resources Institute FinlandVantaaFinland
  3. 3.Institute of Mathematical Problems of BiologyRussian Academy of SciencesPushchinoRussia
  4. 4.Branch of Shemyakin and OvchinnikovInstitute of Bioorganic Chemistry RASPushchinoRussia
  5. 5.Pushchino Municipal AdministrationPushchinoRussia
  6. 6.Institute of Biology of the Komi Science Centre of the Ural DivisionRussian Academy of SciencesSyktyvkarRussia
  7. 7.Bashkir State UniversityUfaRussia

Personalised recommendations